The RAFFn pulses are designed to generate fictitious
fields that allow locking of magnetization in the
rotating frames of rank n. Exchange induced relaxations
during RAFFn pulses for two site exchange were described
using Bloch-McConnell formalism. The results demonstrate
that with the increase of n the sensitivity of RAFFn to
the slow motional regime increases.

Diffusion of water through susceptibility gradients
causes R1dispersion
to a degree that depends on the geometry and size of the
inhomogeneities responsible for the gradients. Finite
difference simulations were run and compared to
experimental data to further substantiate a method to
quantify the spatial scales of packed inhomogeneities
that has been presented in the literature. R1dispersions
were simulated for spherical and cylindrical structures
with varying radii and volume fractions to estimate the
correlation time, a parameter that estimates the scale
of the gradients.

Philipp Emerich1, Alexander Ruh1,
Harald Scherer2, Dmitry S. Novikov3,
and Valerij G. Kiselev11Dept. of Radiology, Medical Physics,
University Medical Center Freiburg, Freiburg, Germany,2Dept.
of Inorganic and Analytical Chemistry, University
Freiburg, Freiburg, Germany,3Bernard
and Irene Schwartz Center for Biomedical Imaging,
Department of Radiology, New York University School of
Medicine, New York, New York, United States

Transverse relaxation in biological tissues is sensitive
to the structural organization of magnetic
inhomogeneities on the cellular level. A recently
developed theory predicts a reflection of this
structural organization in the long-time behavior of the
induced relaxation rate as a power law approach to the
asymptote. We report the first experiment aimed at
verification of this theory in a model system of
microbeads suspended in aqueous solution of variable
magnetic susceptibility. Experimental results are in a
good agreement with theoretical predictions and Monte
Carlo simulations.

3125.

In vivo quantification of
myowater anatomical compartmentation with proton
T2-relaxation studies using a three site two exchange (3S2X)
model

Confirmation of the anatomical compartmentation theory
to explain the biexponential T2-relaxation of bulk-water
in skeletal muscle is motivated by the great clinical
interest on a non-invasive tool for quantification of
myowater distribution in vivo. In vivo T2-relaxation
data were acquired from the soleus of healthy volunteers
at different vascular filling conditions
(vascular-draining, normal and vascular-filling).
Variations on T2-spectra following the different
vascular conditions offered strong evidences in favour
of the anatomical compartmentation theory. Data were
analysed by means of compartmental exchange analysis. A
3S2X model has been shown to be capable of predicting
NMR relaxation data for realistic transmembrane exchange
values.

3126.

Use of L1-norm solution to
Impose Spatial Smoothness Constraints in Quantitative T2
Relaxometry

Problem: A moderately high SNR (~200) QT2R data is
needed for robust tissue-water-fraction-map
reconstruction if L2-norm based spatial smoothness is
implemented. We are testing L1-norm-solver as other
possible candidate. Methods: We are developing
L1-norm-solver in this context and its performance is
compared against L2-norm-solver in context of imposing
spatial constraints. Results & Conclusions: Results
using L2- and L1-norms are similar at high SNR (>200);
however, L2-norm-solver performs better at lower SNR. In
near future, we would develop “hybrid” filter to impose
smoothness and sparsity simultaneously to make L1-norm
performs better at low SNR.

3127.

Accurate T2 Mapping with
Sparisty and Linear Predictability Filtering

Xi Peng1, Leslie Ying2, Xin Liu1,
and Dong Liang11Paul C. Lauterbur Research Centre for
Biomedical Imaging, Shenzhen Key Laboratory for MRI,
Shenzhen Institutes of Advanced Technology, Shenzhen,
Guangdong, China,2Department of Biomedical
Engineering, Department of Electrical Engineering, The
State University of New York at Buffalo, Buffalo, New
York, United States

Accelerating the acquisition of T2 mapping via sparse
sampling has drawn considerable attention. However, due
to non-ideal conditions in practical settings (i.e.,
insufficient sparsity/rank and coherent sampling),
errors occur in the T2-weighted images and the
subsequent relaxation map especially with high reduction
factors and noisy measurements. We address this issue by
integrating the prior information (i.e., exponential
functions) on the temporal signals into the image
reconstruction step. This is in contrast to the
conventional wisdom where the image reconstruction and
parameter mapping are performed independently. The
proposed method was demonstrated with an in-vivo brain
dataset and shows promising results.

We have developed a model-based approach for joint
reconstruction of spin-lattice relaxation timeT1and
proton densityM0maps
from DESPOT1 sequences. Our statistical methods employ
regularization to reduce noise amplification issues
common in conventional least-squares estimators. The
proposed technique dramatically improves mapping
precision and quality, both for synthetic andin
vivodata,
and at a wide range of noise thresholds and flip angle
combinations.

Li Zhao1and
Craig H. Meyer1,21Biomedical Engineering, University of
Virginia, Charlottesville, Virginia, United States,2Radiology,
University of Virginia, Charlottesville, Virginia,
United States

Parameter mapping is essential for clinic diagnose and
its acceleration is highly demanded. With under sampling
in kspace-parameter encoding space, we proposed an
unscented Kalman filter based method to estimation the
parameter directly without reconstruction of the
interval images. This method was verified in accelerated
T2 mapping on numerical phantom and volunteer data.
Comparing to compressed sensing with K-SVD, unscented
Kalman filter provides more accurate T2 map in less
reconstruction time.

A setup for dynamic parameter mapping with a temporal
resolution of up to 7.2s is presented. It uses the
previously presented IR-MAP technique to reconstruct
relaxation curves for successive inversions, each
followed by a radial Look-Locker FLASH acquisition and a
short waiting time for relaxation. After a correction of
T_1 errors caused by an insufficient relaxation between
successive inversions, this allows monitoring T_1
variations over time, which is desirable in many
applications such as dynamic contrast enhanced MRI.
After the functionality of the technique is validated on
a phantom and in vivo, the feasibility of the technique
in dynamic contrast-enhanced MRI is demonstrated in a
brain tumor patient.

Noam Ben-Eliezer1, Daniel K. Sodickson1,
and Kai Tobias Block11Department of Radiology, New York University
School of Medicine, Bernard and Irene Schwartz Center
for Biomedical Imaging, New York, NY, United States

Accurate quantification of T2values
in vivo is a long-standing challenge hampered by the
extensive scan times associated with full Spin-Echo (SE)
acquisitions, or by the inherent bias of rapid multi-SE
sequences resulting from stimulated and indirect echoes.
Recently, a novel proof-of-principle T2mapping
technique – the echo-modulation curve (EMC)
algorithm – has been proposed based on precise Bloch
simulations. In this work we establish the EMC technique
applicability to various body regions, analyze its
accuracy and precision at different SNR levels and
present extensions both to non-Cartesian trajectories
and to multiparametric mapping of T2relaxation,
proton density and transmit B1+profile.

3132.

ASSESSMENT OF IRON OVERLOAD
IN THE LIVER WITH MRI T2*. THE EFFECTS OF THE ANALYSIS
TECHNIQUE ON T2* ESTIMATION

MRI has been established as an effective technique for
evaluating iron overload by measuring T2* in the liver.
Although the process of calculating T2* is conceptually
straightforward, various factors associated with image
analysis could change the resulting measurement,
including the signal averaging method, exponential
fitting model, region-of-interest (ROI) location and
size, echo truncation, iron overload severity, and
inter-/intra-observer variabilities. In this study, we
evaluate the influences of these factors on T2*
estimation in calibrated phantoms and eleven patients
with different degrees of iron overload. The results
show various degrees of similarities and differences
between the performances of different analysis
approaches.

3133.

Which one is most accurate
and has highest precision? - A comprehensive analysis of T2(*)estimation
techniques

MR relaxation parameters are often used to quantify the
state of tissue and to distinguish pathological from
normal conditions. MR magnitude noise can introduce a
serious bias toward higher or lower relaxation
parameters. Such a bias may have serious clinical
consequences, e.g., when relaxation parameters are used
for treatment decisions such as in liver iron overload
diseases. With the current contribution, we aim to give
clear recommendations how to estimate relaxation rates
for different experimental scenarios, such as in slow
and fast relaxing tissues.

3134.

MRI evaluation of the
relationship between R2, R2*, and
tissue iron in the human basal ganglia

Joanna Collingwood1,2, Mary Finnegan1,
Zobair Arya3, Jean-Pierre Hagen1,
Saherabanu Chen1, Alimul Chowdhury4,
Sarah Wayte5, Eddie Ngandwe5,
Naomi Visanji6, Jon Dobson7, Penny
Gowland8, Lili-Naz Hazrati9, and
Charles Hutchinson5,101School of Engineering, University of
Warwick, Coventry, West Midlands, United Kingdom,2Materials
Science and Engineering, University of Florida,
Gainesville, Florida, United States,3Department
of Physics, University of Warwick, West Midlands, United
Kingdom,4School
of Psychology, University of Birmingham, West Midlands,
United Kingdom,5University
Hospitals Coventry and Warwickshire, West Midlands,
United Kingdom,6Morton
and Gloria Shulman Movement Disorders Centre, Toronto
Western Hospital, Ontario, Canada,7J.
Crayton Pruitt Family Department of Biomedical
Engineering, University of Florida, Florida, United
States,8School
of Physics & Astronomy, University of Nottingham,
Nottinghamshire, United Kingdom,9Tanz
Centre for Research in Neurodegenerative Disease,
University of Toronto, Ontario, Canada,10Warwick
Medical School, University of Warwick, West Midlands,
United Kingdom

R2 and R2* were determined for primary regions in the
basal ganglia. Ten adult volunteers were measured at
3.0T and 1.5T on clinical platforms; R2*, R2, and the
field-dependent R2 increase (FDRI) were compared with
previously reported iron concentrations for the same
regions. A set of post-mortem tissues were measured at
9.4T using a Bruker MicWB40; relationships between iron,
R2, and R2* were directly evaluated by mapping tissue
iron distribution with synchrotron X-ray fluorescence,
enabling spatial correlation with MRI maps. These data
indicate that at 9.4T the linear relationship between
both R2 and R2*, and tissue iron concentration, is
preserved.

T2*-weighted MRI has been established for evaluating
myocardial iron overload with strong correlation with
biopsy. The recently introduced dual-energy
computed-tomography (DECT) has the potential for
evaluating iron overload without energy-dependent CT
attenuation or tissue fat effects. This study
investigates the performance of DECT for evaluating
myocardial iron overload (from images acquired at
different diagnostic imaging energies of 80/100/120/140
kVp) and compare the results to MRI T2* based on
experiments on phantoms with calibrated iron
concentrations. DECT showed high accuracy for evaluating
iron overload independent of the implemented imaging
energy, with the results comparable to those from MRI
T2* measurements.

The study investigated the usefulness of the 2D fuzzy
c-mean (FCM) clustering to lower the variability of the
T2* liver iron assessment by separated the vessel pixels
from parenchyma. The manual and 2D-FCM segmentations
were performed on the multi-echo T2* images and their
LIC maps of 60 thalassemia major patients. The 2D FCM
method can correctly segment the parenchyma and vessel
pixels by 95.7±7.9% and 99.5±2.4%, respectively. The
variability of the T2* measurement then can be lower by
32%, but finding the optimal clustering variables are
necessary before it can be practically employed.

Previous MRI studies of brain iron deposition have
estimated R2 and R2* (or R2') simultaneously from
multiple gradient echo sampling of either a single spin
echo or a free induction decay and the left side of a
spin echo. These studies have, explicitly or implicitly,
assumed Lorentzian frequency distributions for the water
resonance. Here, we demonstrate that Gaussian frequency
distributions, which have a markedly different time
domain response, provide a better fit to signals from
brain tissue, leading to a more accurate
characterization of both the reversible and the
irreversible transverse relaxation processes in these
tissues.

3138.

Liver T2* measurements: The
best curve fitting model for ROI based method and Pixel
based method

We compared between median T2*obtained from pixel based
method and the T2* derived from ROI based method in 3
different fitting models, mono-exponential, Offset and
Truncation model. Fifteen β thalassemia major patients
were involved to this study. The results showed strongly
correlation between T2* obtained from two methods with
offset fitting model and there was no significant
difference between the 2 methods with this fitting
model. ROI based method with offset fitting model
potentially provided similar T2* to that of pixel based
method for liver T2* measurements.

The quality of MWF maps obtained with the standard
approach, were compared with results obtained from
measured and scaled flip angle maps in a cohort of 10
healthy young volunteers. Two scaling approaches were
used; an expected 180 degree pulse and scaling to the
first pass fitted FA. The two-step procedure was found
to be a viable approach to improve the MWF maps, without
a too high cost in terms of goodness-of-fit or
distinction between components.

3140.

A framework for getting the
correctT2distribution
from multiple echo magnitude MRI signal

Ruiliang Bai1,2, Cheng Guan Koay3,
and Peter J Basser11Section on Tissue Biophysics and Biomimetics,
PPITS, NICHD, National Institutes of Health, Bethesda,
MD, United States,2Biophysics
Program, Institute for Physical Science and Technology,
University of Maryland, College Park, MD, United States,3Department
of Medical Physics, University of Wisconsin School of
Medicine and Public Health, Madison, WI, United States

The noise-induced bias in the magnitude multi-echo MRI
signals causes artifacts inT2distributions
calculated by conventional inverse Laplace transform
(ILT) algorithms, that implicitly assume the noisy
signal is always Gaussian distributed. Here we propose a
signal transformational framework to map the noisy
Rician-distributed magnitude signal back to a Gaussian
distribution and then perform an ILT algorithm on the
corrected data to obtain an accurateT2distribution.
Both simulations and experiments validate the efficiency
of this approach in correcting these artifacts.

3141.

Myelin Water Imaging using
Direct Visualization of Short Transverse Relaxation Time
Component (ViSTa) at 7T

Sung Suk Oh1, Joon Yul Choi1, and
Jongho Lee11Radiology, University of Pennsylvania,
Philadelphia, PA, United States

A new myelin water imaging method, ViSTa (Direct
Visualization of Short Transverse Relaxation Time
Component) was applied at 7T and compared to 3T. The
ViSTa images at 7T showed a factor of 3 higher SNR than
at 3T, demonstrating potential of using ViSTa at 7T.

We characterized the multi-component transverse
relaxation (T2) decay in egg yolk with high-SNR,
high-quality Carr-Purcell-Meiboom-Gill (CPMG) sequences.
Three T2 components are identified; two fast-decaying
(12 and 23ms) of roughly equal proportion, associated
with water and lipids. The third is a small (2%) slow
component (293ms). The egg yolk is a widely available
phantom material that may prove useful in validating
methods to extract information from short T2 species
like brain myelin-associated water (MAW).

Se-Hong Oh1,2, Joon Yul Choi2,
Yeiji Im2, Thomas Prasloski3, and
Jongho Lee21Imaging Institute, Cleveland Clinic,
Cleveland, Ohio, United States,2Department
of Radiology, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pennsylvania, United States,3Department
of Physics and Astronomy, University of British
Columbia, Vancouver, Canada

In this study, the whole brain MWF map from conventional
MWI (GRASE) was compared to that from a novel MWI
method, Direct Visualization of Short Transverse
Relaxation Time Component (ViSTa). The voxel-wise
correlation shows a high correlation between the two
maps. Compared to the conventional MWI, ViSTa provides
superior image quality with better reproducibility. It
also covers a larger volume in a shorter scan time.

3144.

Assessment of mcDESPOT
Precision Using Constrained Estimation

Samuel Anthony Hurley1and
Andrew L Alexander1,21Medical Physics, University of Wisconsin,
Madison, WI, United States,2Psychiatry,
University of Wisconsin, Madison, WI, United States

Multicomponent relaxation with steady state imaging
(mcDESPOT) method is evaluated using both Monte Carlo
simulations and Cramér–Rao lower bound computations. The
effects of the Gaussian contraction constrained
estimation on the precision of the model are
investigated.

3145.

Multi-Component Fitting of
T2*Relaxation
in White Matter at 3 and 7 Tesla

Previous studies have demonstrated separation of
cellular compartments by utilizing large, local
frequency shifts (Δf) and increased T2*relaxation
at high magnetic field strength (7 T). This abstract
examines the reproducibility of a multi-component
fitting model at 7 T, while also investigating the
feasibility of this method at 3 T. Our findings suggest
the possibility of separating cellular specific
contributions in white matter at both 3 and 7 T.
Quantification of cellular compartments, importantly the
myelin-water fraction, has important implications for
the study of normal aging and disease.

3146.

T2-relaxometry for Myelin
Water Fraction Estimation using a Mixture of Wald
Distributions

We introduce a novel model with small number of
parameters to characterize transverse relaxation rate
spectrum at each voxel. We use mixture of three Wald
distributions with unknown mixture weights, mean and
shape parameters to represent the distribution of the
relative amount of water in between myelin sheets,
tissue water, and cerebrospinal fluid. Wald distribution
has a Gaussian-like distribution with positive support
and a closed form Laplace transform which are
exceptional and distinctive attributes for the
representation of transverse relaxation rate
distribution. The parameters of the model are estimated
using the constrained variable projection method as a
substantial number of unknown parameters is linear.

Myelin Water Fraction (MWF) is computed from
multicomponent relaxation analysis that requires long
acquisition and post-processing times limiting its
practical application in infants. Here we suggest a
novel 2-step strategy for fast MWF quantification. We
fitted a 3-component model (myelin-related water,
intra/extra-cellular water, CSF) with adults’ data
having a large number of measurements to identify the
most appropriate T1 and T2 values for each component
over the whole brain. These values were fixed for the
following MWF quantification with a reduced number of
measurements. Infant MWF maps showed progressive
myelination with age and were in qualitative agreement
with other studies.

A biexponential model can be used to fit
inversion-recovery NMR data to differentiate between
compartmental relaxation times and magnetization
fractions in order to measure compartment-specific
apparent diffusion coefficients. Due to the presence of
noise in acquired data and sensitivity to actual
observed parameter values, the fitted parameters display
different amounts of error depending on whether an
extracellular or intracellular contrast agent is
administered. In this study, simulations of data sets
corresponding to both scenarios were generated to
determine the effects of signal to noise and parameter
limitations on the constraints of fitting by calculating
the root mean square percentage error.